Decision Model of Aero-Engine Design Integration Platform Implementation Solution Selection Based on Number Interval Number with Priority Order

Considering the fuzzy factors in the aero-engine design integration platform implementation solution selection, using the prioritized interval number evaluation method, the implementation model of the aero-engine design integration platform implementation solution selection is established, and the priority relationship is calculated according to the relative distance between each attribute and the ideal point. Through the calculation of the relative distance between the interval value and the negative ideal point, the single evaluation value is obtained. Finally, the comparison result of the pre-selected scheme is obtained by analysing and solving the preferred model. The model comprehensively considers the determining factors in the optimization process and uncertain factors, clear logic, and the best results obtained are comprehensive and reasonable.


Introduction
The main functions of the aero-engine design integration platform are to integrate, package, and call aero-engine design tools, define and manage the aero-engine design process, manage the control relationships and data flows between design tasks, finally, the accumulation, inheritance and reuse of aero-engine design knowledge, concepts, norms and experiences will be realized. Aeroengine design integration platform implementation solution selection decision problem is a multiple attribute decision making problem. Multiple attribute decision making is also called finite-plan multi-objective decisionmaking [1]. It refers to the decision-making problem of selecting the optimal alternative or sorting the scheme when considering multiple attributes. It is the modern decision-making science. An important part. Its theory and methods are widely used in many fields such as engineering, technology, economics, management and military. The main problem solved by multi-attribute decision-making is in the aspects of evaluation and selection. There are common elements in multiple attribute decision making [2-3]: 1. Multiple options: Before making group decisions, decision makers must first measure the number of feasible solutions as an option for evaluation.2. Multiple evaluation attributes: Before making a group decision, the decision maker must first measure the number of feasible attributes and propose several related attributes that affect the plan. The attributes can be independent or related.3. Weight assignment of attributes: Different attribute decision makers have different preference tendencies, and different weights are assigned to different attributes. Generally, the weight distribution of attributes is usually normalized.

Statement of aero-engine design integration platform implementation solution selection decision problem
Aero-engine design integration platform implementation decision problem where the attribute values are represented by the intervals and priority ordering. The following formula can describe the decision problem in detail: In a multi-attribute decision problem, the set of alternatives is Where mn a represents the initial decision indicator value of the n attribute of the m scheme, and the value may be a certain value or a fuzzy value, which may be quantitative or qualitative.
There are three main steps to solve the problem: the first step is to establish an attribute evaluation system, the second step is to determine the attribute weight, and the final step is to use the evaluation method to evaluate the alternative.
The method of attribute value normalization can be divided into two categories, one is the normalization method of deterministic attribute value, and the other is the normalization method of fuzzy attribute value. The canonical methods for determining the attribute values can be divided into linear transformation, extreme transformation, vector transformation, trigonometric transformation, etc. The principle is to distinguish between the benefit attribute and the cost type attribute. However, the normative methods of fuzzy attribute values are more class. For qualitatively characterized control variables, considering the incompleteness of information and the limitations of risk diagnosis expert knowledge, it is often difficult to express their original information with precise numbers, and fuzzy expression. Sometimes it is more conducive to risk diagnosis experts to express their preferences. The representations of fuzzy expression mainly include interval numbers, triangular fuzzy numbers, trapezoidal fuzzy numbers, intuitionistic fuzzy numbers, language scales, and binary semantics. In the decision-making process, although different fuzzy language representations and aggregation methods will be used to obtain different results, there are no advantages or disadvantages in terms of various fuzzy language representations.

Aero-engine design integration platform implementation solution selection decision model
In terms of the attribute j U , Specify priority orderings or ordered vectors In addition, the classification values for the alternatives can be retrieved as follows: Definition 3. The distance between the two attribute values is calculated as following formula:

Solution of aero-engine design integration platform implementation solution selection decision problem
Aero-engine design integration platform implementation decision problem is a typical multi-attribute decision problem with four attributes and five alternatives. According to the algorithm of the third part, the specific data of the decision matrix is obtained as follows: Use the third part of the formula to solve the T value, and then calculate the order of the program: